| Identifying expressions of emotion in text S Aman, S Szpakowicz International Conference on Text, Speech and Dialogue, 196-205, 2007 | 645 | 2007 |
| Cloud-based software platform for big data analytics in smart grids Y Simmhan, S Aman, A Kumbhare, R Liu, S Stevens, Q Zhou, V Prasanna Computing in Science & Engineering 15 (4), 38-47, 2013 | 368 | 2013 |
| Energy management systems: state of the art and emerging trends S Aman, Y Simmhan, VK Prasanna IEEE communications Magazine 51 (1), 114-119, 2013 | 250 | 2013 |
| Using roget’s thesaurus for fine-grained emotion recognition S Aman, S Szpakowicz Proceedings of the Third International Joint Conference on Natural Language …, 2008 | 147 | 2008 |
| Improving energy use forecast for campus micro-grids using indirect indicators S Aman, Y Simmhan, VK Prasanna IEEE International Conference on Data Mining Workshops (ICDMW), 389-397, 2011 | 100 | 2011 |
| Holistic measures for evaluating prediction models in smart grids S Aman, Y Simmhan, VK Prasanna IEEE Transactions on Knowledge and Data Engineering (TKDE) 27 (2), 2015 | 92 | 2015 |
| An informatics approach to demand response optimization in smart grids Y Simmhan, S Aman, B Cao, M Giakkoupis, A Kumbhare, Q Zhou, D Paul, ... Technical report, USC Computer Science 31, 60, 2011 | 91 | 2011 |
| Prediction models for dynamic demand response: Requirements, challenges, and insights S Aman, M Frincu, C Chelmis, M Noor, Y Simmhan, VK Prasanna 2015 IEEE International Conference on Smart Grid Communications …, 2015 | 71 | 2015 |
| Cloud-based software platform for data-driven smart grid management Y Simmhan, S Aman, A Kumbhare, R Liu, S Stevens, Q Zhou, V Prasanna IEEE/AIP computing in science and engineering 79, 2013 | 56 | 2013 |
| Empirical comparison of prediction methods for electricity consumption forecasting S Aman, M Frincu, C Charalampos, U Noor, Y Simmhan, V Prasanna University of Southern California, Tech. Rep, 14-942, 2014 | 39 | 2014 |
| Toward data-driven demand-response optimization in a campus microgrid Y Simmhan, V Prasanna, S Aman, S Natarajan, W Yin, Q Zhou ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Buildings …, 2011 | 33 | 2011 |
| Recognizing emotions in text S Aman University of Ottawa (Canada), 2007 | 28 | 2007 |
| Estimating reduced consumption for dynamic demand response C Chelmis, S Aman, MR Saeed, M Frincu, VK Prasanna Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015 | 13 | 2015 |
| Influence-Driven Model for Time Series Prediction from Partial Observations S Aman, C Chelmis, VK Prasanna AAAI Conference on Artificial Intelligence, 2015 | 13 | 2015 |
| Learning to reduce: A reduced electricity consumption prediction ensemble S Aman, C Chelmis, V Prasanna City of Los Angeles Department, 2016 | 12 | 2016 |
| Addressing data veracity in big data applications S Aman, C Chelmis, V Prasanna 2014 IEEE International Conference on Big Data (Big Data), 1-3, 2014 | 12 | 2014 |
| University of Southern California,“ S Aman, Y Simmhan, VK Prasanna Energy Management Systems: State of the Art and Emerging Trends”, rivista …, 2013 | 10 | 2013 |
| Online Time Series Clustering For Demand Response A Theory to Break the ‘Curse of Dimensionality’ R Pal, C Chelmis, S Aman, M Frincu, V Prasanna ACM e-Energy Conference, 2015 | 9* | 2015 |
| Adaptive energy forecasting and information diffusion for smart power grids Y Simmhan, V Agarwal, S Aman, A Kumbhare, S Natarajan, N Rajguru, ... City of Los Angeles Department, CA (United States), 2012 | 7 | 2012 |
| Enabling automated dynamic demand response: From theory to practice M Frincu, C Chelmis, R Saeed, V Prasanna, S Aman, V Zois, C Fern, ... Proceedings of the 2015 ACM Sixth International Conference on Future Energy …, 2015 | 6 | 2015 |
Viktor K. PrasannaUniversity of Southern CaliforniaBestätigte E-Mail-Adresse bei usc.edu
